Comparison of PlanetScope and Sentinel-2 Spectral Channels and Their Alignment via Linear Regression for Enhanced Index Derivation DOI Creative Commons
Christian Massimiliano Baldin, Vittorio Casella

Geosciences, Journal Year: 2025, Volume and Issue: 15(5), P. 184 - 184

Published: May 20, 2025

Prior research has shown that for specific periods, vegetation indices from PlanetScope and Sentinel-2 (used as a reference) must be aligned to benefit the experience of utilize techniques such data fusion. Even during worst-case scenario, it is possible through histogram matching calibrate achieve same values (useful also proxy). Based on these findings, authors examined effectiveness linear regression in aligning individual bands prior computing determine if are shifted differently. The was conducted five important bands: Red, Green, Blue, NIR, RedEdge. These allow computation well-known like NDVI NDRE, soil Iron Oxide Ratio Coloration Index. Previous showed not sufficient by itself align scenario. However, this paper demonstrates its efficiency achieving accurate band alignment. This finding highlights importance considering scaling requirements obtained different satellite sensors, Sentinel-2. Contemporary images acquired two sensors May July demonstrated behaviors their bands; however, can datasets even problematic month May.

Language: Английский

Comparison of PlanetScope and Sentinel-2 Spectral Channels and Their Alignment via Linear Regression for Enhanced Index Derivation DOI Creative Commons
Christian Massimiliano Baldin, Vittorio Casella

Geosciences, Journal Year: 2025, Volume and Issue: 15(5), P. 184 - 184

Published: May 20, 2025

Prior research has shown that for specific periods, vegetation indices from PlanetScope and Sentinel-2 (used as a reference) must be aligned to benefit the experience of utilize techniques such data fusion. Even during worst-case scenario, it is possible through histogram matching calibrate achieve same values (useful also proxy). Based on these findings, authors examined effectiveness linear regression in aligning individual bands prior computing determine if are shifted differently. The was conducted five important bands: Red, Green, Blue, NIR, RedEdge. These allow computation well-known like NDVI NDRE, soil Iron Oxide Ratio Coloration Index. Previous showed not sufficient by itself align scenario. However, this paper demonstrates its efficiency achieving accurate band alignment. This finding highlights importance considering scaling requirements obtained different satellite sensors, Sentinel-2. Contemporary images acquired two sensors May July demonstrated behaviors their bands; however, can datasets even problematic month May.

Language: Английский

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